A Semi-Soft Label-Guided Network With Self-Distillation for SAR Inshore Ship Detection

Author:

Qin Chuan1ORCID,Wang Xueqian1ORCID,Li Gang1ORCID,He You1ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Autonomous Research Project of the Department of Electronic Engineering, Tsinghua University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference53 articles.

1. Scattering-Keypoint-Guided Network for Oriented Ship Detection in High-Resolution and Large-Scale SAR Images

2. Fine-grained recognition for oriented ship against complex scenes in optical remote sensing images;han;IEEE Trans Geosci Remote Sens,2021

3. Domain Adaptation for Semi-Supervised Ship Detection in SAR Images

4. Center-boundary dual attention for oriented object detection in remote sensing images;liu;IEEE Trans Geosci Remote Sens,2021

5. Ship detection in SAR images based on an improved faster R-CNN

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